Deqin Zhao

Title: Innovations of Deqin Zhao in Analog Circuit Fault Diagnosis

Introduction

Deqin Zhao is a prominent inventor based in Anhui, China. He has made significant contributions to the field of analog circuit fault diagnosis, holding a total of 4 patents. His work focuses on developing methods that enhance the accuracy and efficiency of fault classification in analog circuits.

Latest Patents

One of his latest patents is an "Analog-circuit fault diagnosis method based on continuous wavelet analysis and ELM neural network." This innovative method involves several steps, including data acquisition through Multisim simulation to obtain an output response data set. It utilizes continuous wavelet analysis to extract features from the data, forming feature vectors that represent corresponding faults. The method is designed to implement accurate and quick fault classification using an ELM network, demonstrating improved effectiveness in extracting circuit fault features.

Another notable patent is the "Analog circuit fault mode classification method." This method outlines a systematic approach to classify fault modes in analog circuits. It includes collecting voltage signal sample vectors, extracting fault characteristic vectors, and constructing a fault mode classifier based on a support vector machine. The classifier is noted for its simplicity in learning and training, as well as its reliability in mode classification accuracy.

Career Highlights

Deqin Zhao is affiliated with Hefei University of Technology, where he continues to advance research in his field. His work has garnered attention for its practical applications in improving the reliability of analog circuits.

Collaborations

He has collaborated with notable colleagues, including Yigang He and Zhijie Yuan, contributing to the advancement of knowledge and technology in circuit fault diagnosis.

Conclusion

Deqin Zhao's innovative approaches to analog circuit fault diagnosis have established him as a key figure in the field. His patents reflect a commitment to enhancing the accuracy and efficiency of fault classification methods, making significant strides in the realm of electrical engineering.